Bridging Conservation and Human-Wildlife Conflict for Coexistence

Bridging Conservation and Human-Wildlife Conflict for Coexistence | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Bridging Conservation and Human-Wildlife Conflict for Coexistence Dinesh Neupane, Bhagawan Raj Dahal, Prakash Chandra Aryal, Sunjeep Pun, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7233040/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Human-wildlife conflict (HWC) poses a significant threat to conservation, particularly in the region, where increasing wildlife populations intersect with dense human communities. This study examines the HWC scenario in one of the protected areas (Parsa National Park) of Terai Arc Landscape, where a growing population of large mammals shares the resources in highly populated buffer zone. Analyzing official relief claims from the past five years (2018/19–2022/23) as indicators of damage intensity, the study found that elephants were involved in 45% of conflicts, followed by leopards at 29% and tigers at 13.5%. Trend analysis revealed the increasing trend in herbivore-related damage while decreasing trend of carnivore-related conflict, despite the increase in tiger population within the study area. Human settlements displayed species-specific hotspots with no overlap, suggesting that species tend to avoid areas occupied by competitors and predators. Financial claims totaled NPR 9.47 million (~ USD 80,275; with an average of ~ NPR 2 million per year), predominantly for elephant-related incidents (55%). However, there was significant difference in relief claim amount among trophic groups (F 2, 448 = 4.308, p = 0.014). Statistical analysis showed that conflict intensity, expressed as relief claims, increased with greater distance from buffer zone forests (β = 0.0008, t = 2.6, p < 0.01) and significantly associated with tiger (β = 0.52, t = 3.8, p < 0.01). Additionally, distance from water sources has non-linear relationship with conflict, being low in the distance of 1.5km. These findings underscore the need for habitat management interventions, such as enhancing water availability within protected areas and maintaining corridors to connect the park's source populations with sink populations in degraded buffer zone and national forests. Implementing a field-based assessment process for wildlife-related damage could support human-wildlife coexistence in the region. Corridor habitat restoration carnivore herbivore human-wildlife coexistence relief mechanism Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Human-wildlife conflict is an increasing concern in conservation (König et al. 2020 ), driven by intensified competition for resources between humans and animals (Nyhus 2016 , Waters et al. 2016 ). Factors such as habitat fragmentation, increased human encroachment, and rising wildlife populations have exacerbated this conflict in many regions (Billah et al. 2021 , Woodroffe 2000 ), particularly in the areas with growing population of both human and wildlife. The intensity and frequency of conflicts vary depending on the species involved and their movement patterns. For instance, elephants can cause property damage, crop destruction, and even human casualties, while tigers are known for livestock predation and human attacks. Additionally, intensity of such impact is more prevalent when large mammals such as elephants, rhino, tiger, and leopard requiring greater home range and resources (Ripple et al. 2014 ) are packed in high densities in small, but island type protected areas (Wikramanayake et al. 2004 ). In such situations, agricultural fields and livestock provide alternative resources for wildlife’s daily needs of food and nutrition (Mekonen 2020 ), where human practices in agriculture, their behavior and livestock rearing exacerbate the wildlife problem in the region (Neupane et al. 2017 , Sharma and Neupane 2023 ) resulting more frequent encounters between human and animals. Prevention or mitigation of conflict is challenging when multiple endangered species of conservation importance are involved (Acharya et al., 2016 ). Nepal has seen notable success in boosting wildlife populations over the past decade, particularly those reside in Terai Arc landscape (TAL), with significant increases in the numbers of tigers (from 121 to 355), elephants (from 142 to > 200), and rhinos (from 534 to 752) over the last 15 years (DNPWC 2024 , DNPWC and DoFSC 2022; Ram and Acharya 2020 ). This growth means that wildlife now requires more resources for food and shelter. Given the limited and sometimes encroached natural habitats, this increased demand can lead to heightened conflicts with human populations. Studies have shown that Nepal has been experiencing rising conflicts with major wildlife species in recent years (Ram et al. 2021 , Acharya et al. 2016 ). Such situations can cultivate negative attitudes towards wildlife and may lead to retaliatory killings as people protect their property and lives. Terai Arc Landscape (TAL) in Nepal and India is one of the priority landscapes where diverse wildlife including various endangered large mammals, occur in high densities (Wikramanayake et al. 2004 ). With high human density and increasing wildlife populations (National Statistics Office 2024 ), human-wildlife conflict is a growing concern in the Terai Arc Landscape (Jhala et al. 2020 , DNPWC 2017, Karki et al. 2015 , Chanchani et al. 2014 ). The increasing occurrence of human-wildlife conflict in the Terai Arc Landscape in Nepal has also had an impact on the conservation of endangered species. There are occasional incidents of retaliatory killing of these animals (Ram et al. 2022 , DNPWC 2017, Neupane et al. 2013 ). However, specific areas might exhibit different trends of human-wildlife conflict, which is a focus of exploration in this study. To prevent and mitigate the increasing human-wildlife conflicts in and around Nepal’s protected areas, the government introduced the buffer zone concept in 1996 (Budhathoki 2004 ). Subsequently, Nepal initiated to provide relief to victims of wildlife damage from 1996, however, it has been formalized with wildlife damage relief guidelines in 2013 (MoFE 2013 ). People started to report the loss from wildlife (primarily attacks to human and livestock depredation) to the respective protected areas through buffer zone user committees after the initiation of the relief scheme. The Nepalese government has been proactive in frequently updating both the relief amounts and the list of species eligible for compensation. The fifth amendment of these guidelines in 2023 expanded the scope to include 16 species, now covering damage caused by blue bulls and monkeys (MoFE 2023 ). Despite these efforts, relying solely on financial relief is not a sustainable solution. A comprehensive, data-driven management strategy is needed to effectively address conflict and promote coexistence between humans and wildlife within the buffer zones. The Central Terai region of Nepal, known as Madhesh Province, supports a diverse range of large mammals, including tigers, leopards, rhinos, and elephants, within Parsa National Park (PNP) and its adjacent forests. This province, which has the second highest human population density in Nepal, shows notable characteristics including 59% of households use firewood as their main energy source, 89% are engaged in subsistence farming, and 36% are illiterate (National Statistics Office 2024 ). People's culture and profession, as well as factors like season and human density, all play a role in the dynamics of human-wildlife conflict. Additionally, the number of iconic wildlife has increased in the last 15 years in PNP with a 50% increase in elephant population (DNPWC/MoFSC/GoN 2009 , Ram and Acharya 2020 ) and 925% increase in tiger number (DNPWC 2023 ). In response to the increasing wildlife population and corresponding conflict, the Government of Nepal expanded the park’s boundaries by 128.39km 2 eastward into Bara District in 2015. PNP is an important protected area that provides critical connectivity for wildlife movement between the Valmiki Tiger Reserve in India, Chitwan National Park in Nepal, and national forests to the north. This connectivity enables spillover wildlife populations to share habitat within PNP, making it essential to understand wildlife movement, conservation challenges, and effective management interventions. Given this context, managing human-wildlife conflict has become a critical priority for park officials to foster a harmonious relationship between the park and local communities. Identifying the key factors contributing to human-wildlife conflict in this area is essential for effective mitigation strategies and promoting human-wildlife coexistence. Study area This study focuses on investigating the human-wildlife conflict (HWC) in and around Parsa National Park (area: 912.69 km 2 ). Situated in the south-central lowlands, Parsa National Park spans the Madhesh and Bagmati provinces and includes parts of the Parsa, Bara, and Makawanpur districts (Fig. 1 ). It is adjacent to Chitwan National Park to the west, national forests to the east and north, and the Valmiki Tiger Reserve in India to the southwest. The park's predominantly tropical and subtropical forests are largely made up of Sal trees, which account for about 90% of the vegetation. This habitat supports several endangered species, including the Asian elephant, tiger, sloth bear, and leopard. The buffer zone surrounding Parsa National Park (area: 285.3 km 2 ) is a legally designated area intended to provide forest resources to local communities and mitigate the impact and pressure on the park from local activities, and vice versa. Buffer zone around Parsa National Park includes two sub-metropolitan cities (Hetauda and Jitpur-Simara) and three rural municipalities (Manahari, Thori, and Jirabhawani) across the three districts. Within this buffer zone, 55% of the land is forested, 30% is used for agriculture, while grasslands, shrublands, and water bodies are relatively limited (PNP 2018 ). Methods We gathered official records of relief claims reported to the Parsa National Park office from 2018/19 to 2022/23 to analyze trends and patterns in human-wildlife conflict (HWC). The records provide detailed information on each incident, including the victim's name, age, sex, address, date, type of incident/loss, and the claimed and received relief amounts. These relief claim and received amount helped us assess the severity of HWC, as incident frequency alone did not fully capture the intensity of the problem. For instance, a single human casualty can be far more severe than multiple instances of crop damage. The data was categorized into four types of losses: (a) human casualty (death and injury), (b) property damage, (c) livestock depredation (buffalo, cattle, goat, sheep, pig, duck/chicken), and (d) crop raiding. We also classified the wildlife involved by trophic level: carnivores (tiger, leopard), herbivores (elephant, rhino), and omnivores (wild boar). To analyze the data, we calculated the claim amounts for each category of wildlife, conflict type, and fiscal year using averages and standard deviations. The claim amounts, received relief funds, and the difference between claims and received funds were compared across wildlife categories and fiscal years using the Kruskal-Wallis test with effects, as parametric assumptions were not met. We used a generalized additive model (GAM) with the mgcv R package (Wood, 2017 ) where wildlife was treated as a factor, while water distance was used as smooth function. Other variables, including park distance, buffer zone forest distance was included as linear predictors. Due to the skewed nature of the response variable, we adopted a multiplicative approach with a gamma distribution for the model. Variables were used without standardization for ease of interpretation. We started with a complex model and concluded with a simplified one using Akaike information criteria. Results Human-Wildlife Conflict scenario Relief claims for damages in the buffer zone of Parsa National Park were exclusively made for incidents involving five species: elephants, leopard, rhino, tiger, and wild boar. Damages caused by other species were not eligible for claims due to the limited provisions set by the government for compensation. Between the fiscal years 2018/19 and 2022/23, a total of 454 human-wildlife conflict cases were reported. Elephants were responsible for most of these conflicts, accounting for 45%, followed by leopards (29%) and tigers (13.5%). The predominant types of damage reported were crop loss and livestock depredation (Fig. 2 ). In terms of human casualties, elephants were responsible for all three recorded deaths (n = 3) and 42% of the injuries over the five-year period. Tigers contributed 25% of human injuries, while rhinos and leopards each accounted for 8%. Notably, there has been a shift in conflicts, with herbivore-related incidents, particularly crop damage, showing an increase, while carnivore-related conflicts, especially those involving livestock depredation, have seen a decline (Fig S1 ). Spatial distribution of the conflict Majority of the conflict occurred particularly in Manahari Rural Municipality (RM) in the northern buffer zone, and Jirabhawani Rural Municipality in the southern buffer zone. Human-elephant conflict and human-tiger conflict hotspots lie in Manahari Rural Municipality, while human-leopard conflict occurred in Jirabhawani RM. Wild boar related conflict was found in different administrative subunits of the buffer zone of Parsa National Park than that of the tiger related conflict (Fig. 3 ). Relief distribution Between 2018/19 and 2022/23, Parsa National Park received relief claims totaling NPR 9.47 million (~ USD 80,275, with an exchange rate of USD 1 = NPR 118 as of January 1, 2022). The government provided NPR 8.27 million (~ USD 70,063), averaging USD 14,000 per year in relief. The majority of the claimed amount (55%) was for damage caused by elephants, followed by leopards (21%) and tigers (12%) (Table S1 ). On average, the claimed amount was consistently higher than the amount received, with the largest discrepancies observed in property damage. In approximately two-thirds of cases, there was no difference between the claimed and received relief amounts, with the maximum discrepancy reaching NPR 90,000. For claims below NPR 14,000, the variation between the claimed and received amounts reached 75% (Fig. S2). The average claim amount differed significantly between wildlife species involved in the conflict (χ²=34.21, df = 4, p < 0.01, η²=0.07), with elephants having the lowest average claim (NPR 11,200 ± 8,291), followed by leopards (NPR 14,694 ± 11,135), rhinos (NPR 21,225 ± 36,705), tigers (NPR 19,766 ± 20,370), and wild boars (NPR 17,900 ± 37,689). Additionally, claims were significantly higher for carnivore-related damages (NPR 16,270 ± 14,774) compared to herbivore-related damages (NPR 12,873 ± 19,014) (χ²=26.96, df = 1, p < 0.01, η²=0.057). Regarding conflict type, the highest average claims were for human injuries (NPR 49,070 ± 71,442), followed by livestock loss (NPR 16,298 ± 14,840), with other damages averaging just over ten thousand, showing significant variation (χ²=36.1, df = 4, p < 0.01, η²=0.07). Among the years, the lowest average claim was in FY 2018/19 (NPR 10,689 ± 3,714), and the highest was in FY 2021/22 (NPR 17,558 ± 23,167), with significant variation between years (χ²=42.13, df = 5, p < 0.01, η²=0.08). Variables influencing HWC related claim amount in the Buffer zone of PNP The model shows that the predicted HWC damage claim amount increased slightly but significantly with an increase in the distance to buffer zone (BZ) forests (Table 1 ). Specifically, a unit increase in BZ forest distance led to approximately a 0.074% increase in the claim amount (β = 0.0007, t = 2.6, p < 0.01). Regarding the wildlife involved, claims related to tigers were significantly higher, with a 68% increase in the claim amount (β = 0.52, t = 3.82, p < 0.001) compared to those involving elephants. Claims related to wild boars were approximately 37% higher than those related to elephants, with marginal significance (β = 0.32, t = 1.83, p = 0.06). While claims for tiger led damages are significant, the claim amounts for leopard, rhino, and wild boar effects are not statistically strong. The effective degrees of freedom (~ 7) indicate that the smoothed term for water distance has a significant but non-linear relationship with the claim amount (F = 3.4, p < 0.001, Table 1 ). This entails fluctuating expected claim amounts in reference to the water distance being the lowest claim for the distance of 1.5 km from water sources (Fig. 4 , Table 1 ). Table 1 Model summary for expected amounts of claims for HWC events considering distance and wildlife factors. Claim amounts related to elephant damage were referenced as interception in the model. The significance of smoothed water distance (edf. of ~ 7) shows a non-linear relationship with claim amounts in and around PNP. Predictor Estimate Std. Error t-value p-value Intercept 0.0499 0.0827 0.6040 0.5464 BZF Distance (km) 0.0008 0.0003 2.6150 0.0092 Leopard 0.0942 0.1439 0.6550 0.5130 Rhino 0.3407 0.2315 1.4720 0.1418 Tiger 0.5213 0.1362 3.8290 0.0001 Wild boar 0.3163 0.1722 1.8370 0.0669 Smooth Term edf Ref.df F-value p-value Water Distance (km) 7.087 7.842 3.41 < 0.001 *** Discussion Human-wildlife conflict scenario and its distribution This study provides a thorough analysis of the dynamics of human-wildlife conflict (HWC) in the buffer zone of Parsa National Park, Nepal, from 2018/19 to 2022/23. The findings indicate that elephants are the main instigators of conflict, responsible for approximately 45% of reported incidents. In comparison, leopards and tigers account for 29% and 14% of conflicts, respectively. Notably, the research identifies a significant increase in conflicts involving herbivores, while those related to carnivores have substantially decreased. This shift can be attributed to Nepal's commitment to the TX2 initiative, launched in 2010, which has focused substantial conservation efforts and funding on boosting tiger populations and reducing human-tiger conflict (DNPWC, 2016 ). Consequently, Parsa National Park has benefited from tiger-centered conservation projects (PNP 2018 ) that have proven effective in mitigating human-tiger conflict. The study also examined the spatial distribution of human-wildlife conflict within the buffer zone of Parsa National Park. It reveals that conflicts involving prey species, such as wild boar, do not overlap spatially with those involving predators like tigers and leopards within administrative units. This separation suggests a behavioral tendency of prey species to avoid areas that are heavily frequented by their predators, supporting the hypothesis that prey species exhibit avoidance behaviors to minimize the risk of predation (Sommers and Chesson 2019 , Lima and Dill 1990 ). Northern buffer zone and some administrative units in southern section of buffer zone were the hotspot for species-specific HWC. The buffer zone of Parsa National Park is characterized by a significant amount of forest cover, particularly in its northern section, which connects the park to the national forest from neighboring protected areas from Nepal and India (PNP, 2018 ). This extensive forest habitat is crucial for maintaining source-sink dynamics but creates a shared space where humans and wildlife compete for resources, leading to conflicts. Human-wildlife conflict and social dimension The intensity of damage from human-wildlife conflict (HWC) has profound socio-economic implications, particularly for marginalized communities. These communities, heavily reliant on agriculture, livestock rearing, and forest resources for their livelihoods, are especially vulnerable to the impacts of HWC (Lamichhane et al., 2018). Historical migration patterns, particularly those following malaria eradication initiatives in the Terai, have deepened their dependency on local forest resources (Sapkota and Odén, 2008 ). Consequently, many of these communities live near wildlife habitats, placing them at an increased risk of conflict. Furthermore, the lack of adequate infrastructure—such as durable housing and protective measures for livestock—further exposes these communities to damage from elephants and other herbivores. This vulnerability is compounded by their socio-economic status, proximity to wildlife, and insufficient protective measures, all of which intensify the challenges in managing HWC risks. Studies indicate that hill migrants, predominantly from ethnic communities, tend to settle near forests with limited landholdings (Gartaula et al., 2014 ). Their heavy reliance on forest resources is closely tied to their economic status, family size, and proximity to forests (Sapkota and Odén, 2008 ). These ethnic and marginalized groups also tend to have larger family sizes and higher poverty rates compared to other castes (Subba et al., 2014 ). Additionally, their increased interaction with wildlife can be linked to traditional land and home-use practices, which are known to attract wildlife (Neupane et al., 2017 ). Relief mechanisms - variation in relief claimed and received amount Another critical aspect of the study is its analysis of the discrepancies between relief claims submitted by affected individuals and the actual compensation they receive. The findings indicate that this gap is closely related to the inflexible nature of Nepal's relief guidelines, which impose upper limits on compensation for specific types of damages, regardless of the actual losses incurred. For example, the revised relief guidelines of 2069 (with the fifth amendment in 2079) set relief caps at NPR 1,000,000 for human fatalities, NPR 10,000 to NPR 60,000 for livestock losses, NPR 10,000 for crop damage, and NPR 20,000 for livestock sheds (MoFE 2023 ). These caps often leave affected individuals feeling undervalued and dissatisfied, particularly in cases involving crop and property losses (Pathak et al. 2024 , Rai et al. 2023 ). To improve the effectiveness of relief mechanisms, the study suggests the need for a more nuanced approach that includes field-based evaluations of damages. A community-based insurance scheme could serve as a viable and time-efficient solution (Sherchan et al. 2022 ), allowing for a more accurate evaluation of losses and ensuring that compensation aligns with the actual impacts on the affected communities. Habitat Components and Conflict Intensity Conflict intensity has been closely linked to specific habitat components, including proximity to water sources and the extent of forest cover. The research shows that conflict incidents are low in the distance of 1.5 km from water resources, but higher in nearer or further distances indicating increased competition for resources in these areas. Additionally, the region's porous geology exacerbates the situation by limiting water retention, often resulting in dry conditions for much of the year (Lamichhane et al. 2018a ). Therefore, restoring and enhancing water sources within protected areas could serve as a strategic method for mitigating human-wildlife conflict. Furthermore, the study highlights that distance from forested areas is positively correlated with conflict intensity, particularly regarding elephants. As landscape animals (Davidar et al. 2023 , Chan et al. 2022 ), elephants require expansive habitats that can cover several hundred square kilometers for their nomadic movements (Campos-Arceiz et al. 2022 ). Thus, it is not surprising that conflicts arise in areas that are relatively distant from the buffer forest. To tackle this issue, prioritizing wildlife corridor management is essential. Creating secure passages for elephants and other wildlife can help reduce direct interactions with human settlements, thereby minimizing conflict and promoting coexistence. Conclusion and Recommendations In conclusion, this study underscores the complexity of human-wildlife conflict in the buffer zone of Parsa National Park, emphasizing the multifaceted challenges faced by marginalized communities. Effective strategies for mitigating HWC must take into account the socio-economic contexts of affected populations, the ecological dynamics at play, and the necessity for adaptive management practices in relief distribution. As the claim amounts tend to be higher for tiger and away from BZ forest areas, the mitigation measures should take special attention while implementing conservation intervention. For example, people in the further distance from buffer forests also need to be incorporated in awareness, and other mitigative measures. Collaborative efforts among government agencies, conservation organizations, and local communities will be essential in addressing these challenges, fostering a sustainable coexistence between humans and wildlife in this biodiverse region. Establishing wildlife corridor in the northern buffer zone and safe passage for wildlife along with livelihood interventions for local communities could support the prevention and mitigation of human-wildlife conflict in the area. Incorporating community input into conservation planning, conducting field-based damages assessments and maximizing compensation for damages can foster a more resilient framework that benefits both people and wildlife. Additionally, implementing a wildlife damage insurance mechanism could provide a viable solution. Declarations Competing Interests There are no competing interests among authors. Ethical Approval This study neither involves human subjects in a trial nor does interviews with them. Thus, this declaration is not application. Clinical trial number This declaration is not applicable. Funding This research was funded by Darwin Initiative [Funding number 29 − 011]. Author Contribution Author contributions DN: Data mining and analysis, conceptualizing, drafting, reviewing.BRD: Drafting and reviewingPCA: Data analysis, drafting, and reviewingSP: Data mining, and draftingMB: Drafting and reviewingAP: Drafting and reviewingSKT: Drafting and reviewingBPT: Drafting and reviewingAP: Drafting and reviewingRW: Drafting and reviewingPM: Drafting and reviewingHA: Drafting and reviewing Acknowledgement We are grateful to the Department of National Parks and Wildlife Conservation and Parsa National Park for providing research permission and data sources. We appreciate Mr. Santosh K. Bhagat (Conservation Officer) for his coordination, and the staff of Parsa National Park and the Buffer Zone User Committees for their assistance in providing data. 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Ecology and evolution , 11 (17), 11639–11650. Ram, A. K., Yadav, N. K., Subedi, N., Pandav, B., Mondol, S., Khanal, B., Kharal, D. K., Acharya, H. B., Dhakal, B. K., Acharya, K. P., & Baral, H. S. (2022). Landscape predictors of human elephant conflicts in Chure Terai Madhesh Landscape of Nepal (Vol. 7, p. 100458). Environmental Challenges. Core Team, R. (2022). R: A Language and Environment for Statistical Computing . R Foundation for Statistical Computing. Ripple, W. J., Estes, J. A., Beschta, R. L., Wilmers, C. C., Ritchie, E. G., Hebblewhite, M., Berger, J., Elmhagen, B., Letnic, M., Nelson, M. P., & Schmitz, O. J. (2014). Status and ecological effects of the world’s largest carnivores. Science, 343(6167), p.1241484. Sapkota, I. P., & Odén, P. C. (2008). Household characteristics and dependency on community forests in Terai of Nepal. International journal of social forestry , 1 (2), 123–144. Sharma, B., & Neupane, D. (2023). Enhancing human-tiger coexistence in forest corridors of Nepal through a socio-ecological approach to conservation. Trees, Forests and People, 13, p.100402. Sherchan, R., Rai, R. K., Rai, R., & Dhakal, A. (2022). Designing a community-based insurance scheme to reduce human–wildlife conflict. Environment Development and Sustainability , 24 (4), 5112–5130. Sommers, P., & Chesson, P. (2019). Effects of predator avoidance behavior on the coexistence of competing prey. The American Naturalist , 193 (5), E132–E148. Subba, C., Pyakuryal, B., Bastola, T. S., Subba, M. K., Raut, N. K., & Karki, B. (2014). A study on the socio-economic status of indigenous peoples in Nepal . Lawyer’s Association for Human Rights of Nepalese Indigenous Peoples (LAHURNIP). Waters, C. N., Zalasiewicz, J., Summerhayes, C., Barnosky, A. D., Poirier, C., et al. (2016). The Anthropocene is functionally and stratigraphically distinct from the Holocene. Science , 351 (6269), aad2622. Wikramanayake, E., McKnight, M., Dinerstein, E., Joshi, A., Gurung, B., & Smith, D. (2004). Designing a conservation landscape for tigers in human-dominated environments. Conservation Biology , 18 (3), 839–844. https://doi.org/10.1111/j.1523-1739.2004.00145.x Wood, S. N. (2017). Generalized additive models: an introduction with R . chapman and hall/CRC. Woodroffe, R. (2000). Predators and people: using human densities to interpret declines of large carnivores. Animal conservation , 3 (2), 165–173. Woodroffe, R., Thirgood, S., & Rabinowitz, A. (Eds.). (2005). People and wildlife, conflict or co-existence? (Vol. 9). Cambridge University Press. Additional Declarations No competing interests reported. Supplementary Files Supplementarytableandfigures.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 06 Aug, 2025 Editor assigned by journal 06 Aug, 2025 Submission checks completed at journal 06 Aug, 2025 First submitted to journal 28 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7233040","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":496674355,"identity":"c52e6914-6d3c-4111-95ce-6e8c623517c6","order_by":0,"name":"Dinesh Neupane","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYDCCw0DM2ADn2jAwsJOoJY2BgZmQlgOoWg4T1sJ3nPfgw587GPL4JXIPfi6oOG8v38zA+LjiF24tkof5ko15zzAUS87IS5aeceY2s8FhBmbDs324tRgc5jGTZmxjSNxwI8dAmrftNpsBMwObZGMPXi3mP38Ctey/kWP8m/ffOR6gwwhqMWPgBdkikWMmzdtwQAIYAmySDT/w+YXHGOgeicQZZ96lWfMcSzYwOMzYbNjYgFsL3/kzhh9/ttkk9rfnHr7NU2NnL9/efPBhwx/cWqBAAoh5YBxgNAEDhBjAg8whbMsoGAWjYBSMHAAA4YFMt2Np/GgAAAAASUVORK5CYII=","orcid":"","institution":"Zoological Society of London, Nepal Programme","correspondingAuthor":true,"prefix":"","firstName":"Dinesh","middleName":"","lastName":"Neupane","suffix":""},{"id":496674356,"identity":"a1053de6-3d2b-44ad-acbc-c5b424f61b12","order_by":1,"name":"Bhagawan Raj Dahal","email":"","orcid":"","institution":"Zoological Society of London, Nepal Programme","correspondingAuthor":false,"prefix":"","firstName":"Bhagawan","middleName":"Raj","lastName":"Dahal","suffix":""},{"id":496674357,"identity":"6b52f02f-bc25-4c8e-b867-20df3946c3d5","order_by":2,"name":"Prakash Chandra Aryal","email":"","orcid":"","institution":"Goldengate International College","correspondingAuthor":false,"prefix":"","firstName":"Prakash","middleName":"Chandra","lastName":"Aryal","suffix":""},{"id":496674358,"identity":"ef3dc6c3-3ed1-42cf-a00e-335d27a61497","order_by":3,"name":"Sunjeep Pun","email":"","orcid":"","institution":"Zoological Society of London, Nepal Programme","correspondingAuthor":false,"prefix":"","firstName":"Sunjeep","middleName":"","lastName":"Pun","suffix":""},{"id":496674359,"identity":"c15fafdf-26c5-4234-a1c3-1ed885fac425","order_by":4,"name":"Maheshwor Basnet","email":"","orcid":"","institution":"Zoological Society of London, Nepal 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Programme","correspondingAuthor":false,"prefix":"","firstName":"Bishnu","middleName":"Prasad","lastName":"Thapaliya","suffix":""},{"id":496674363,"identity":"2b0e520a-ff20-4087-914c-bdc1fa415583","order_by":8,"name":"Asmita Pandey","email":"","orcid":"","institution":"Zoological Society of London, Nepal Programme","correspondingAuthor":false,"prefix":"","firstName":"Asmita","middleName":"","lastName":"Pandey","suffix":""},{"id":496674364,"identity":"dfd908c9-9420-4ad4-87e3-e8149106caa5","order_by":9,"name":"Ramchandra Khatiwada","email":"","orcid":"","institution":"Parsa National Park","correspondingAuthor":false,"prefix":"","firstName":"Ramchandra","middleName":"","lastName":"Khatiwada","suffix":""},{"id":496674365,"identity":"94f46f8b-226a-4fec-b46d-2de2b7a38dff","order_by":10,"name":"Prachanda Maharjan","email":"","orcid":"","institution":"Zoological Society of London, Nepal Programme","correspondingAuthor":false,"prefix":"","firstName":"Prachanda","middleName":"","lastName":"Maharjan","suffix":""},{"id":496674366,"identity":"795fa29f-2af4-4b22-ba35-f2b17e93bbaf","order_by":11,"name":"Haribhadra Acharya","email":"","orcid":"","institution":"Department of National Parks and Wildlife Conservation","correspondingAuthor":false,"prefix":"","firstName":"Haribhadra","middleName":"","lastName":"Acharya","suffix":""}],"badges":[],"createdAt":"2025-07-28 10:53:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7233040/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7233040/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88808165,"identity":"77f109a3-ae7d-4f2a-a335-a4932451af3a","added_by":"auto","created_at":"2025-08-11 15:14:23","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":89429,"visible":true,"origin":"","legend":"\u003cp\u003eMap showing the buffer zone forest, national forest and administrative units in the buffer zone of Parsa National Park, Nepal.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7233040/v1/6176f827e587a67b6673887d.jpeg"},{"id":88808858,"identity":"fb87b14d-3929-44fa-b6e5-0ec6c364589a","added_by":"auto","created_at":"2025-08-11 15:22:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42334,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of HWC incidents occurred based on years (a), wildlife involved (b), and conflict type (c) in the buffer zone of Parsa National Park, Nepal for a period of five year (2018-2022).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7233040/v1/ce8a37c39bfcab317055ff60.png"},{"id":88808170,"identity":"6abd91d5-0c14-400e-a727-d35b16990c84","added_by":"auto","created_at":"2025-08-11 15:14:23","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":225289,"visible":true,"origin":"","legend":"\u003cp\u003eSpatial distribution of overall human wildlife conflict and species-specific conflict in the buffer zone of Parsa National Park of Nepal.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7233040/v1/6b1c1562aff75e69f2684735.png"},{"id":88810124,"identity":"0b299f01-cd19-4534-838c-be570a061615","added_by":"auto","created_at":"2025-08-11 15:30:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":134152,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship of relief amount claims with (a) water source distance, buffer zone forest distance and (c) wildlife involved in HWC.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7233040/v1/2eda6e85d407bbc2207d678c.png"},{"id":88810137,"identity":"9db86f33-c10f-4352-8f90-3f09479f561a","added_by":"auto","created_at":"2025-08-11 15:30:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1150779,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7233040/v1/3790c76a-c9db-4407-9755-f305e40532ee.pdf"},{"id":88808168,"identity":"2a6f738d-dbc7-4a6c-9789-efdae4dc8467","added_by":"auto","created_at":"2025-08-11 15:14:23","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":111691,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytableandfigures.docx","url":"https://assets-eu.researchsquare.com/files/rs-7233040/v1/30f61fac622aee27cbf7608f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Bridging Conservation and Human-Wildlife Conflict for Coexistence","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman-wildlife conflict is an increasing concern in conservation (König et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), driven by intensified competition for resources between humans and animals (Nyhus \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e, Waters et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Factors such as habitat fragmentation, increased human encroachment, and rising wildlife populations have exacerbated this conflict in many regions (Billah et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Woodroffe \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2000\u003c/span\u003e), particularly in the areas with growing population of both human and wildlife. The intensity and frequency of conflicts vary depending on the species involved and their movement patterns. For instance, elephants can cause property damage, crop destruction, and even human casualties, while tigers are known for livestock predation and human attacks. Additionally, intensity of such impact is more prevalent when large mammals such as elephants, rhino, tiger, and leopard requiring greater home range and resources (Ripple et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) are packed in high densities in small, but island type protected areas (Wikramanayake et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). In such situations, agricultural fields and livestock provide alternative resources for wildlife’s daily needs of food and nutrition (Mekonen \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), where human practices in agriculture, their behavior and livestock rearing exacerbate the wildlife problem in the region (Neupane et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, Sharma and Neupane \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) resulting more frequent encounters between human and animals. Prevention or mitigation of conflict is challenging when multiple endangered species of conservation importance are involved (Acharya et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNepal has seen notable success in boosting wildlife populations over the past decade, particularly those reside in Terai Arc landscape (TAL), with significant increases in the numbers of tigers (from 121 to 355), elephants (from 142 to \u0026gt; 200), and rhinos (from 534 to 752) over the last 15 years (DNPWC \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, DNPWC and DoFSC 2022; Ram and Acharya \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This growth means that wildlife now requires more resources for food and shelter. Given the limited and sometimes encroached natural habitats, this increased demand can lead to heightened conflicts with human populations. Studies have shown that Nepal has been experiencing rising conflicts with major wildlife species in recent years (Ram et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Acharya et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Such situations can cultivate negative attitudes towards wildlife and may lead to retaliatory killings as people protect their property and lives.\u003c/p\u003e\u003cp\u003eTerai Arc Landscape (TAL) in Nepal and India is one of the priority landscapes where diverse wildlife including various endangered large mammals, occur in high densities (Wikramanayake et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). With high human density and increasing wildlife populations (National Statistics Office \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), human-wildlife conflict is a growing concern in the Terai Arc Landscape (Jhala et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, DNPWC 2017, Karki et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, Chanchani et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The increasing occurrence of human-wildlife conflict in the Terai Arc Landscape in Nepal has also had an impact on the conservation of endangered species. There are occasional incidents of retaliatory killing of these animals (Ram et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, DNPWC 2017, Neupane et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, specific areas might exhibit different trends of human-wildlife conflict, which is a focus of exploration in this study. To prevent and mitigate the increasing human-wildlife conflicts in and around Nepal’s protected areas, the government introduced the buffer zone concept in 1996 (Budhathoki \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Subsequently, Nepal initiated to provide relief to victims of wildlife damage from 1996, however, it has been formalized with wildlife damage relief guidelines in 2013 (MoFE \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). People started to report the loss from wildlife (primarily attacks to human and livestock depredation) to the respective protected areas through buffer zone user committees after the initiation of the relief scheme. The Nepalese government has been proactive in frequently updating both the relief amounts and the list of species eligible for compensation. The fifth amendment of these guidelines in 2023 expanded the scope to include 16 species, now covering damage caused by blue bulls and monkeys (MoFE \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Despite these efforts, relying solely on financial relief is not a sustainable solution. A comprehensive, data-driven management strategy is needed to effectively address conflict and promote coexistence between humans and wildlife within the buffer zones.\u003c/p\u003e\u003cp\u003eThe Central Terai region of Nepal, known as Madhesh Province, supports a diverse range of large mammals, including tigers, leopards, rhinos, and elephants, within Parsa National Park (PNP) and its adjacent forests. This province, which has the second highest human population density in Nepal, shows notable characteristics including 59% of households use firewood as their main energy source, 89% are engaged in subsistence farming, and 36% are illiterate (National Statistics Office \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). People's culture and profession, as well as factors like season and human density, all play a role in the dynamics of human-wildlife conflict. Additionally, the number of iconic wildlife has increased in the last 15 years in PNP with a 50% increase in elephant population (DNPWC/MoFSC/GoN \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2009\u003c/span\u003e, Ram and Acharya \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and 925% increase in tiger number (DNPWC \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In response to the increasing wildlife population and corresponding conflict, the Government of Nepal expanded the park’s boundaries by 128.39km\u003csup\u003e2\u003c/sup\u003e eastward into Bara District in 2015. PNP is an important protected area that provides critical connectivity for wildlife movement between the Valmiki Tiger Reserve in India, Chitwan National Park in Nepal, and national forests to the north. This connectivity enables spillover wildlife populations to share habitat within PNP, making it essential to understand wildlife movement, conservation challenges, and effective management interventions.\u003c/p\u003e\u003cp\u003eGiven this context, managing human-wildlife conflict has become a critical priority for park officials to foster a harmonious relationship between the park and local communities. Identifying the key factors contributing to human-wildlife conflict in this area is essential for effective mitigation strategies and promoting human-wildlife coexistence.\u003c/p\u003e"},{"header":"Study area","content":"\u003cp\u003eThis study focuses on investigating the human-wildlife conflict (HWC) in and around Parsa National Park (area: 912.69 km\u003csup\u003e2\u003c/sup\u003e). Situated in the south-central lowlands, Parsa National Park spans the Madhesh and Bagmati provinces and includes parts of the Parsa, Bara, and Makawanpur districts (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It is adjacent to Chitwan National Park to the west, national forests to the east and north, and the Valmiki Tiger Reserve in India to the southwest. The park's predominantly tropical and subtropical forests are largely made up of Sal trees, which account for about 90% of the vegetation. This habitat supports several endangered species, including the Asian elephant, tiger, sloth bear, and leopard.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe buffer zone surrounding Parsa National Park (area: 285.3 km\u003csup\u003e2\u003c/sup\u003e) is a legally designated area intended to provide forest resources to local communities and mitigate the impact and pressure on the park from local activities, and vice versa. Buffer zone around Parsa National Park includes two sub-metropolitan cities (Hetauda and Jitpur-Simara) and three rural municipalities (Manahari, Thori, and Jirabhawani) across the three districts. Within this buffer zone, 55% of the land is forested, 30% is used for agriculture, while grasslands, shrublands, and water bodies are relatively limited (PNP \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe gathered official records of relief claims reported to the Parsa National Park office from 2018/19 to 2022/23 to analyze trends and patterns in human-wildlife conflict (HWC). The records provide detailed information on each incident, including the victim's name, age, sex, address, date, type of incident/loss, and the claimed and received relief amounts. These relief claim and received amount helped us assess the severity of HWC, as incident frequency alone did not fully capture the intensity of the problem. For instance, a single human casualty can be far more severe than multiple instances of crop damage.\u003c/p\u003e\u003cp\u003eThe data was categorized into four types of losses: (a) human casualty (death and injury), (b) property damage, (c) livestock depredation (buffalo, cattle, goat, sheep, pig, duck/chicken), and (d) crop raiding. We also classified the wildlife involved by trophic level: carnivores (tiger, leopard), herbivores (elephant, rhino), and omnivores (wild boar). To analyze the data, we calculated the claim amounts for each category of wildlife, conflict type, and fiscal year using averages and standard deviations. The claim amounts, received relief funds, and the difference between claims and received funds were compared across wildlife categories and fiscal years using the Kruskal-Wallis test with effects, as parametric assumptions were not met.\u003c/p\u003e\u003cp\u003eWe used a generalized additive model (GAM) with the mgcv R package (Wood, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) where wildlife was treated as a factor, while water distance was used as smooth function. Other variables, including park distance, buffer zone forest distance was included as linear predictors. Due to the skewed nature of the response variable, we adopted a multiplicative approach with a gamma distribution for the model. Variables were used without standardization for ease of interpretation. We started with a complex model and concluded with a simplified one using Akaike information criteria.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eHuman-Wildlife Conflict scenario\u003c/b\u003e\u003c/p\u003e\u003cp\u003eRelief claims for damages in the buffer zone of Parsa National Park were exclusively made for incidents involving five species: elephants, leopard, rhino, tiger, and wild boar. Damages caused by other species were not eligible for claims due to the limited provisions set by the government for compensation. Between the fiscal years 2018/19 and 2022/23, a total of 454 human-wildlife conflict cases were reported. Elephants were responsible for most of these conflicts, accounting for 45%, followed by leopards (29%) and tigers (13.5%). The predominant types of damage reported were crop loss and livestock depredation (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In terms of human casualties, elephants were responsible for all three recorded deaths (n\u0026thinsp;=\u0026thinsp;3) and 42% of the injuries over the five-year period. Tigers contributed 25% of human injuries, while rhinos and leopards each accounted for 8%. Notably, there has been a shift in conflicts, with herbivore-related incidents, particularly crop damage, showing an increase, while carnivore-related conflicts, especially those involving livestock depredation, have seen a decline (Fig \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eSpatial distribution of the conflict\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMajority of the conflict occurred particularly in Manahari Rural Municipality (RM) in the northern buffer zone, and Jirabhawani Rural Municipality in the southern buffer zone. Human-elephant conflict and human-tiger conflict hotspots lie in Manahari Rural Municipality, while human-leopard conflict occurred in Jirabhawani RM. Wild boar related conflict was found in different administrative subunits of the buffer zone of Parsa National Park than that of the tiger related conflict (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eRelief distribution\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBetween 2018/19 and 2022/23, Parsa National Park received relief claims totaling NPR 9.47\u0026nbsp;million (~\u0026thinsp;USD 80,275, with an exchange rate of USD 1\u0026thinsp;=\u0026thinsp;NPR 118 as of January 1, 2022). The government provided NPR 8.27\u0026nbsp;million (~\u0026thinsp;USD 70,063), averaging USD 14,000 per year in relief. The majority of the claimed amount (55%) was for damage caused by elephants, followed by leopards (21%) and tigers (12%) (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). On average, the claimed amount was consistently higher than the amount received, with the largest discrepancies observed in property damage. In approximately two-thirds of cases, there was no difference between the claimed and received relief amounts, with the maximum discrepancy reaching NPR 90,000. For claims below NPR 14,000, the variation between the claimed and received amounts reached 75% (Fig. S2).\u003c/p\u003e\u003cp\u003eThe average claim amount differed significantly between wildlife species involved in the conflict (χ\u0026sup2;=34.21, df\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, η\u0026sup2;=0.07), with elephants having the lowest average claim (NPR 11,200\u0026thinsp;\u0026plusmn;\u0026thinsp;8,291), followed by leopards (NPR 14,694\u0026thinsp;\u0026plusmn;\u0026thinsp;11,135), rhinos (NPR 21,225\u0026thinsp;\u0026plusmn;\u0026thinsp;36,705), tigers (NPR 19,766\u0026thinsp;\u0026plusmn;\u0026thinsp;20,370), and wild boars (NPR 17,900\u0026thinsp;\u0026plusmn;\u0026thinsp;37,689). Additionally, claims were significantly higher for carnivore-related damages (NPR 16,270\u0026thinsp;\u0026plusmn;\u0026thinsp;14,774) compared to herbivore-related damages (NPR 12,873\u0026thinsp;\u0026plusmn;\u0026thinsp;19,014) (χ\u0026sup2;=26.96, df\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, η\u0026sup2;=0.057). Regarding conflict type, the highest average claims were for human injuries (NPR 49,070\u0026thinsp;\u0026plusmn;\u0026thinsp;71,442), followed by livestock loss (NPR 16,298\u0026thinsp;\u0026plusmn;\u0026thinsp;14,840), with other damages averaging just over ten thousand, showing significant variation (χ\u0026sup2;=36.1, df\u0026thinsp;=\u0026thinsp;4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, η\u0026sup2;=0.07). Among the years, the lowest average claim was in FY 2018/19 (NPR 10,689\u0026thinsp;\u0026plusmn;\u0026thinsp;3,714), and the highest was in FY 2021/22 (NPR 17,558\u0026thinsp;\u0026plusmn;\u0026thinsp;23,167), with significant variation between years (χ\u0026sup2;=42.13, df\u0026thinsp;=\u0026thinsp;5, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, η\u0026sup2;=0.08).\u003c/p\u003e\u003cp\u003e\u003cb\u003eVariables influencing HWC related claim amount in the Buffer zone of PNP\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe model shows that the predicted HWC damage claim amount increased slightly but significantly with an increase in the distance to buffer zone (BZ) forests (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Specifically, a unit increase in BZ forest distance led to approximately a 0.074% increase in the claim amount (β\u0026thinsp;=\u0026thinsp;0.0007, t\u0026thinsp;=\u0026thinsp;2.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Regarding the wildlife involved, claims related to tigers were significantly higher, with a 68% increase in the claim amount (β\u0026thinsp;=\u0026thinsp;0.52, t\u0026thinsp;=\u0026thinsp;3.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those involving elephants. Claims related to wild boars were approximately 37% higher than those related to elephants, with marginal significance (β\u0026thinsp;=\u0026thinsp;0.32, t\u0026thinsp;=\u0026thinsp;1.83, p\u0026thinsp;=\u0026thinsp;0.06). While claims for tiger led damages are significant, the claim amounts for leopard, rhino, and wild boar effects are not statistically strong.\u003c/p\u003e\u003cp\u003eThe effective degrees of freedom (~\u0026thinsp;7) indicate that the smoothed term for water distance has a significant but non-linear relationship with the claim amount (F\u0026thinsp;=\u0026thinsp;3.4, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This entails fluctuating expected claim amounts in reference to the water distance being the lowest claim for the distance of 1.5 km from water sources (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eModel summary for expected amounts of claims for HWC events considering distance and wildlife factors. Claim amounts related to elephant damage were referenced as interception in the model. The significance of smoothed water distance (edf. of ~\u0026thinsp;7) shows a non-linear relationship with claim amounts in and around PNP.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePredictor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0499\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0827\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5464\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBZF Distance (km)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.6150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0092\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeopard\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.0942\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1439\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.6550\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.5130\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRhino\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.2315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.4720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1418\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTiger\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.5213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1362\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.8290\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild boar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.3163\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1722\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.8370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0669\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmooth Term\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eedf\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRef.df\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWater Distance (km)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.842\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001 ***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cb\u003eHuman-wildlife conflict scenario and its distribution\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study provides a thorough analysis of the dynamics of human-wildlife conflict (HWC) in the buffer zone of Parsa National Park, Nepal, from 2018/19 to 2022/23. The findings indicate that elephants are the main instigators of conflict, responsible for approximately 45% of reported incidents. In comparison, leopards and tigers account for 29% and 14% of conflicts, respectively. Notably, the research identifies a significant increase in conflicts involving herbivores, while those related to carnivores have substantially decreased. This shift can be attributed to Nepal's commitment to the TX2 initiative, launched in 2010, which has focused substantial conservation efforts and funding on boosting tiger populations and reducing human-tiger conflict (DNPWC, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Consequently, Parsa National Park has benefited from tiger-centered conservation projects (PNP \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) that have proven effective in mitigating human-tiger conflict.\u003c/p\u003e\u003cp\u003eThe study also examined the spatial distribution of human-wildlife conflict within the buffer zone of Parsa National Park. It reveals that conflicts involving prey species, such as wild boar, do not overlap spatially with those involving predators like tigers and leopards within administrative units. This separation suggests a behavioral tendency of prey species to avoid areas that are heavily frequented by their predators, supporting the hypothesis that prey species exhibit avoidance behaviors to minimize the risk of predation (Sommers and Chesson \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e, Lima and Dill \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1990\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNorthern buffer zone and some administrative units in southern section of buffer zone were the hotspot for species-specific HWC. The buffer zone of Parsa National Park is characterized by a significant amount of forest cover, particularly in its northern section, which connects the park to the national forest from neighboring protected areas from Nepal and India (PNP, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This extensive forest habitat is crucial for maintaining source-sink dynamics but creates a shared space where humans and wildlife compete for resources, leading to conflicts.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHuman-wildlife conflict and social dimension\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe intensity of damage from human-wildlife conflict (HWC) has profound socio-economic implications, particularly for marginalized communities. These communities, heavily reliant on agriculture, livestock rearing, and forest resources for their livelihoods, are especially vulnerable to the impacts of HWC (Lamichhane et al., 2018). Historical migration patterns, particularly those following malaria eradication initiatives in the Terai, have deepened their dependency on local forest resources (Sapkota and Odén, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Consequently, many of these communities live near wildlife habitats, placing them at an increased risk of conflict.\u003c/p\u003e\u003cp\u003eFurthermore, the lack of adequate infrastructure—such as durable housing and protective measures for livestock—further exposes these communities to damage from elephants and other herbivores. This vulnerability is compounded by their socio-economic status, proximity to wildlife, and insufficient protective measures, all of which intensify the challenges in managing HWC risks.\u003c/p\u003e\u003cp\u003eStudies indicate that hill migrants, predominantly from ethnic communities, tend to settle near forests with limited landholdings (Gartaula et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Their heavy reliance on forest resources is closely tied to their economic status, family size, and proximity to forests (Sapkota and Odén, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). These ethnic and marginalized groups also tend to have larger family sizes and higher poverty rates compared to other castes (Subba et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Additionally, their increased interaction with wildlife can be linked to traditional land and home-use practices, which are known to attract wildlife (Neupane et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eRelief mechanisms - variation in relief claimed and received amount\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAnother critical aspect of the study is its analysis of the discrepancies between relief claims submitted by affected individuals and the actual compensation they receive. The findings indicate that this gap is closely related to the inflexible nature of Nepal's relief guidelines, which impose upper limits on compensation for specific types of damages, regardless of the actual losses incurred. For example, the revised relief guidelines of 2069 (with the fifth amendment in 2079) set relief caps at NPR 1,000,000 for human fatalities, NPR 10,000 to NPR 60,000 for livestock losses, NPR 10,000 for crop damage, and NPR 20,000 for livestock sheds (MoFE \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These caps often leave affected individuals feeling undervalued and dissatisfied, particularly in cases involving crop and property losses (Pathak et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e, Rai et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To improve the effectiveness of relief mechanisms, the study suggests the need for a more nuanced approach that includes field-based evaluations of damages. A community-based insurance scheme could serve as a viable and time-efficient solution (Sherchan et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), allowing for a more accurate evaluation of losses and ensuring that compensation aligns with the actual impacts on the affected communities.\u003c/p\u003e\u003cp\u003e\u003cb\u003eHabitat Components and Conflict Intensity\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflict\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eintensity has been closely linked to specific habitat components, including proximity to water sources and the extent of forest cover. The research shows that conflict incidents are low in the distance of 1.5 km from water resources, but higher in nearer or further distances indicating increased competition for resources in these areas. Additionally, the region's porous geology exacerbates the situation by limiting water retention, often resulting in dry conditions for much of the year (Lamichhane et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018a\u003c/span\u003e). Therefore, restoring and enhancing water sources within protected areas could serve as a strategic method for mitigating human-wildlife conflict.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFurthermore, the study highlights that distance from forested areas is positively correlated with conflict intensity, particularly regarding elephants. As landscape animals (Davidar et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, Chan et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), elephants require expansive habitats that can cover several hundred square kilometers for their nomadic movements (Campos-Arceiz et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Thus, it is not surprising that conflicts arise in areas that are relatively distant from the buffer forest. To tackle this issue, prioritizing wildlife corridor management is essential. Creating secure passages for elephants and other wildlife can help reduce direct interactions with human settlements, thereby minimizing conflict and promoting coexistence.\u003c/p\u003e"},{"header":"Conclusion and Recommendations","content":"\u003cp\u003eIn conclusion, this study underscores the complexity of human-wildlife conflict in the buffer zone of Parsa National Park, emphasizing the multifaceted challenges faced by marginalized communities. Effective strategies for mitigating HWC must take into account the socio-economic contexts of affected populations, the ecological dynamics at play, and the necessity for adaptive management practices in relief distribution. As the claim amounts tend to be higher for tiger and away from BZ forest areas, the mitigation measures should take special attention while implementing conservation intervention. For example, people in the further distance from buffer forests also need to be incorporated in awareness, and other mitigative measures. Collaborative efforts among government agencies, conservation organizations, and local communities will be essential in addressing these challenges, fostering a sustainable coexistence between humans and wildlife in this biodiverse region. Establishing wildlife corridor in the northern buffer zone and safe passage for wildlife along with livelihood interventions for local communities could support the prevention and mitigation of human-wildlife conflict in the area. Incorporating community input into conservation planning, conducting field-based damages assessments and maximizing compensation for damages can foster a more resilient framework that benefits both people and wildlife. Additionally, implementing a wildlife damage insurance mechanism could provide a viable solution.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are no competing interests among authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study neither involves human subjects in a trial nor does interviews with them. Thus, this declaration is not application.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis declaration is not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by Darwin Initiative [Funding number 29\u0026thinsp;\u0026minus;\u0026thinsp;011].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthor contributions DN: Data mining and analysis, conceptualizing, drafting, reviewing.BRD: Drafting and reviewingPCA: Data analysis, drafting, and reviewingSP: Data mining, and draftingMB: Drafting and reviewingAP: Drafting and reviewingSKT: Drafting and reviewingBPT: Drafting and reviewingAP: Drafting and reviewingRW: Drafting and reviewingPM: Drafting and reviewingHA: Drafting and reviewing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to the Department of National Parks and Wildlife Conservation and Parsa National Park for providing research permission and data sources. We appreciate Mr. Santosh K. Bhagat (Conservation Officer) for his coordination, and the staff of Parsa National Park and the Buffer Zone User Committees for their assistance in providing data. We also highly appreciate the Darwin Initiative for their financial support for the execution of the conservation project, from which we gathered the data to produce this research paper. Importantly, we are thankful to the anonymous reviewers for their constructive comments on the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be provided upon request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAcharya, K. P., Paudel, P. K., Neupane, P. R., \u0026amp; K\u0026ouml;hl, M. (2016). 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Cambridge University Press.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"human-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"huec","sideBox":"Learn more about [Human Ecology](http://link.springer.com/journal/10745)","snPcode":"10745","submissionUrl":"https://submission.nature.com/new-submission/10745/3","title":"Human Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Corridor, habitat restoration, carnivore, herbivore, human-wildlife coexistence, relief mechanism","lastPublishedDoi":"10.21203/rs.3.rs-7233040/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7233040/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHuman-wildlife conflict (HWC) poses a significant threat to conservation, particularly in the region, where increasing wildlife populations intersect with dense human communities. This study examines the HWC scenario in one of the protected areas (Parsa National Park) of Terai Arc Landscape, where a growing population of large mammals shares the resources in highly populated buffer zone. Analyzing official relief claims from the past five years (2018/19\u0026ndash;2022/23) as indicators of damage intensity, the study found that elephants were involved in 45% of conflicts, followed by leopards at 29% and tigers at 13.5%. Trend analysis revealed the increasing trend in herbivore-related damage while decreasing trend of carnivore-related conflict, despite the increase in tiger population within the study area. Human settlements displayed species-specific hotspots with no overlap, suggesting that species tend to avoid areas occupied by competitors and predators. Financial claims totaled NPR 9.47\u0026nbsp;million (~\u0026thinsp;USD 80,275; with an average of ~\u0026thinsp;NPR 2\u0026nbsp;million per year), predominantly for elephant-related incidents (55%). However, there was significant difference in relief claim amount among trophic groups (F\u003csub\u003e2, 448\u003c/sub\u003e = 4.308, p\u0026thinsp;=\u0026thinsp;0.014). Statistical analysis showed that conflict intensity, expressed as relief claims, increased with greater distance from buffer zone forests (β\u0026thinsp;=\u0026thinsp;0.0008, t\u0026thinsp;=\u0026thinsp;2.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and significantly associated with tiger (β\u0026thinsp;=\u0026thinsp;0.52, t\u0026thinsp;=\u0026thinsp;3.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Additionally, distance from water sources has non-linear relationship with conflict, being low in the distance of 1.5km. These findings underscore the need for habitat management interventions, such as enhancing water availability within protected areas and maintaining corridors to connect the park's source populations with sink populations in degraded buffer zone and national forests. Implementing a field-based assessment process for wildlife-related damage could support human-wildlife coexistence in the region.\u003c/p\u003e","manuscriptTitle":"Bridging Conservation and Human-Wildlife Conflict for Coexistence","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 15:14:19","doi":"10.21203/rs.3.rs-7233040/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2025-08-06T14:38:59+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-06T04:22:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-06T04:21:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"Human Ecology","date":"2025-07-28T10:48:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"human-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"huec","sideBox":"Learn more about [Human Ecology](http://link.springer.com/journal/10745)","snPcode":"10745","submissionUrl":"https://submission.nature.com/new-submission/10745/3","title":"Human Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"70d330c6-8121-433a-9f4b-0e4032bbb3a8","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-07T14:38:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 15:14:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7233040","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7233040","identity":"rs-7233040","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}